Search Results - "Jun'ichi, Kazama"

EXPLOITING SUBTREES IN AUTO-PARSED DATA TO IMPROVE DEPENDENCY PARSING by Chen, Wenliang, Kazama, Jun'ichi, Uchimoto, Kiyotaka, Torisawa, Kentaro

“…Dependency parsing has attracted considerable interest from researchers and developers in natural language processing. However, to obtain a high‐accuracy…”
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Maximum Entropy Models with Inequality Constraints: A Case Study on Text Categorization by Kazama, Jun’ichi, Tsujii, Jun’ichi

“…Data sparseness or overfitting is a serious problem in natural language processing employing machine learning methods. This is still true even for the maximum…”
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Organizing the Web's Information Explosion to Discover Unknown Unknowns by Torisawa, Kentaro, De Saeger, Stijn, Kazama, Jun’ichi, Sumida, Asuka, Noguchi, Daisuke, Kakizawa, Yasunori, Murata, Masaki, Kuroda, Kow, Yamada, Ichiro

“…This paper introduces the TORISHIKI-KAI project, which aims to construct a million-word-scale semantic network from the Web using state of the art knowledge…”
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Bitext Dependency Parsing With Auto-Generated Bilingual Treebank by Wenliang Chen, Kazama, J., Min Zhang, Tsuruoka, Y., Yujie Zhang, Yiou Wang, Torisawa, K., Haizhou Li

“…This paper proposes a method to improve the accuracy of bilingual texts (bitexts) dependency parsing by using an auto-generated bilingual treebank created with…”
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Maximum entropy models with inequality constraints : A case study on text categorization: Machine Learning in Speech and Language Technologies by KAZAMA, Junichi, TSUJII, Junichi

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Large Scale Relation Acquisition Using Class Dependent Patterns by De Saeger, S., Torisawa, K., Kazama, J., Kuroda, K., Murata, M.

“…This paper proposes a minimally supervised method for acquiring high-level semantic relations such as causality and prevention from the Web. Our method learns…”
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Large scale similarity-based relation expansion by Tsuchidal, Masaaki, De Saeger, Stijn, Torisawa, Kentaro, Murata, Masaki, Kazama, Jun'ichi, Kuroda, Kow, Ohwada, Hayato

“…Recent advances in automatic knowledge acquisition methods make it possible to construct massive knowledge bases of semantic relations, containing information…”
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The NICT concept dictionary by Stijin, De Saeger, Kentaro, Torisawa, Jun'ichi, Kazama, Kiyonori, Ohtake, Isrvan, Varga, Yulan, Yan

“…Summary form only given. In this demonstration we present a system that guides a user's information search (or knowledge discovery) by displaying, in a…”
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TORISHIKI-KAI, An Autogenerated Web Search Directory by Torisawa, Kentaro, De Saeger, Stijn, Kakizawa, Yasunori, Kazama, Jun'ichi, Murata, Masaki, Noguchi, Daisuke, Sumida, Asuka

“…With this research we present a system that suggests valuable complementary information relevant to a user's topic of interest, in the form of keywords. For…”
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Enriching Multilingual Language Resources by Discovering Missing Cross-Language Links in Wikipedia by Oh, Jong-Hoon, Kawahara, Daisuke, Uchimoto, Kiyotaka, Kazama, Jun'ichi, Torisawa, Kentaro

“…We present a novel method for discovering missing cross-language links between English and Japanese Wikipedia articles. We collect candidates of missing…”
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Generating information-rich taxonomy from Wikipedia by Yamada, I, Hashimoto, C, Jong-Hoon Oh, Torisawa, K, Kuroda, K, De Saeger, S, Tsuchida, M, Kazama, J

“…Even though hyponymy relation acquisition has been extensively studied, "how informative such acquired hyponymy relations are" has not been sufficiently…”
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